Project Summary Current methods for assessing prostate cancer, the second most common cause of cancer death in men, do not adequately distinguish between aggressive and indolent disease. Over- or under-treatment due to suboptimal diagnostics can lead to unnecessary loss of life or devastating decline in quality of life. New methods that better assess disease aggressiveness could substantially reduce long-term costs and improve the quality of life of men affected by prostate cancer. Dynamic nuclear polarization (DNP) of [1-13C]-pyruvate provides a greater than 10,000-fold increase in sensitivity to readout by magnetic resonance, allowing insight into biochemical processes in vivo with unprecedented spatiotemporal resolution. Pyruvate lies at a branching point in metabolism that is affected by many cancers: the chemical conversion of pyruvate to lactate is often upregulated by cancer, even under normoxic conditions. HP pyruvate is converted into HP lactate by enzymes that have been shown to correlate with disease aggressiveness. Thus, metabolic MR imaging of HP pyruvate and lactate provides an unprecedented new window of opportunity for minimally invasive diagnostic assessment of disease and aggressiveness. A recent Phase I clinical trial conducted by colleagues at the University of California in San Francisco demonstrated the safety and feasibility of HP pyruvate for assessing patients with prostate cancer. The imaging methods that were used in the feasibility trial demonstrated successful visualization of disease, but provided limited spatial coverage and spatiotemporal resolution. Our goal is to develop and translate new acquisition and analysis strategies for HP 13C MR metabolic imaging that provide the necessary coverage and resolution to enable robust clinical assessment of prostate cancer patients at multiple institutions. This partnership between MD Anderson Cancer Center and UCSF leverages expertise at both institutions to develop and translate new imaging techniques to address currently unmet clinical needs in the management of prostate cancer. The work will be carried out in three Aims. First, we will develop new accelerated dynamic 3D imaging methods that support <0.5cm3 image resolution throughout the gland, along with a new class of dynamic multispectral imaging phantoms to characterize and validate the performance of imaging sequences. In the second Aim, we will refine and integrate pharmacokinetic (PK) analysis algorithms for quantitative assessment of kPL, the imaging biomarker for tumor metabolism, and leverage PK models to further improve the spatiotemporal resolution of HP 13C prostate cancer exams by constrained image reconstruction. In the final Aim, we will assess sensitivity, specificity, and reproducibility of these measurements using a test-retest paradigm and by comparison of imaging with gold-standard histopathology. By the end of this project, we will have implemented robust new imaging methods, and conducted first-ever evaluation of the sensitivity, specificity, and reproducibility of HP 13C metabolic MRI, providing crucial data to help guide future clinical trials for assessing the clinical roles of this technology.